Assessing the comparative advantage of Hawaii’s agricultural exports to the US mainland market

It is conventional economic wisdom that a region produces and exports products that have a comparative advantage (CA). While CA is dynamic, the common measures of CA (such as Balassa’s revealed comparative advantage index and its variants) are static and not comparable over time. This paper adopts an alternate measure to assess the dynamics of CA, utilizing the normalized revealed comparative advantage (NRCA) index. By applying Hawaii’s agricultural exports to the US mainland market as a case study during the period of 1995–2005, this paper illustrates how the NRCA index can systematically assess CA from three perspectives: (1) the static CA patterns, identifying which Hawaii agricultural products have comparative advantage; (2) the changes in CA, identifying which Hawaii agricultural products gain or lose CA; and (3) the trends of CA, identifying which Hawaii agricultural products exhibit statistically significant trends in gaining or losing CA.     

Improving the Quality of Information Flows in the Backend of a Product Development Process: a Case Study

Considerable research has gone into designing effective product development processes. This, coupled with the increasing need for products that are able to deliver reliable, complex functionality with a high degree of innovation, presents a major challenge to modern day industries in the business of developing products. In order to incorporate relevant field experience in the design and manufacturing of new products, increasingly detailed information needs to be retrieved from the market in a very short amount of time. In one particular consumer electronics industry, business process models describing the information flow in the backend of the product development process indicated massive data loss and also serious data quality degradation. This paper attempts to show how such losses can be mitigated and also proposes a business model that can adequately capture information of a higher quality and in a more structured manner. The end result will be a product development process that provides better feedback on current product performance and is more responsive to future market needs. Copyright © 2005 John Wiley & Sons, Ltd.     

Low temperature glass-to-glass wafer bonding

In this paper, results of successful anodic bonding between glass wafers at low temperature are reported. Prior to bonding, a special technique was used, i.e., an amorphous and hydrogen free silicon film was deposited on one of the glass wafers using a sputtering technique. The effects of bonding temperature and voltage were investigated. The bonding temperature and the voltage applied ranged from 200/spl deg/C to 300/spl deg/C and 200 V to 1000 V, respectively. As the bonding temperature and bonding voltage increased, both the unbonded area and the size of voids decreased. Scanning electron microscope (SEM) observations show that the two glass wafers are tightly bonded. The bond strength is higher than 10 MPa for all the bonding conditions. Furthermore, the bond strength increases with increasing bonding temperature and voltage. The study indicates that high temperature and voltage cause more Na/sup +/ ions to neutralize at the negative electrode, which leads to higher charge density inside the glass wafer. Furthermore, the transition period to the equilibrium state also becomes shorter. It is concluded that the anodic bonding mechanisms involve both oxidation of silicon film and the hydrogen bonding between hydroxyl groups.     

Kinetics of copper drift in low-κ polymer interleveldielectrics

This paper addresses the drift of copper ions (Cu⁺) in various low-permittivity (low-κ) polymer dielectrics to identify copper barrier requirements for reliable interconnect integration in future ULSI. Stressing at temperatures of 150-275°C and electric fields up to 1.5 MV/cm was conducted on copper-insulator-silicon capacitors to investigate the penetration of Cu⁺ into the polymers. The drift properties of Cu⁺ in six industrially relevant low-κ organic polymer insulators-parylene-F, benzocyclobutene, fluorinated polyimide, an aromatic hydrocarbon, and two varieties of poly(arylene ether)-were evaluated and compared by capacitance-voltage, current-time, current-voltage, and dielectric time-to-failure measurements. Our study shows that Cu⁺ drifts readily into fluorinated polyimide and poly(arylene ether), more slowly into parylene-F, and even more slowly into benzocyclobutene. Among these polymers, the copper drift barrier property appears to be improved by increased polymer crosslinking and degraded by polar functional groups in the polymers. A thin nitride cap layer can stop the drift. A physical model has been developed to explain the kinetics of Cu⁺ drift     

Effects of Azadirachta excelsa on feeding behaviour,body weight and mortality of Crocidolomia binotalis Zeller (Lepidoptera: Pyralidae)

We investigated the effects of methanolic extracts of Azadirachta excelsa wood (SWE) at concentrations of 5, 10 and 20 g l^?1 against Crocidolomia binotalis. Second instars were fed a diet of cabbage leaves treated with SWE or were contacted topically with SWE. The results indicated that SWE produced significant (p < 0.05) antifeedant and contact toxicity effects. However, among the different treatments, a lesser effect on pupal weight was noted in the contact toxicity test. In most instances, untreated leaves were severely damaged, whereas leaves treated with SWE were not attacked or were only slightly damaged. Although both methods of SWE treatment caused a significantly high mortality rate, there was no difference in dose response in the range studied. Thus SWE at a concentration of 5 g l^?1 was shown to be as active as that at 20 g l^?1. The results indicate that SWE is a potent antifeedant and also has toxicity against C binotalis. Copyright © 2003 Society of Chemical Industry     

Quality of Information Flow in the Backend of a Product Development Process: a Case Study

The increasing need for products that are able to reliably deliver complex functionality with a high degree of innovation presents a major challenge to the modern day product creation processes. In order to be able to use information on the field behaviour of previous products in the design of new products, increasingly detailed information needs to be retrieved from the market in an increasingly shorter time. The purpose of this study is to analyse, in a typical case in the consumer electronics industry, whether the underlying business process is able to generate this information with adequate quality sufficiently quickly. Information models of the company's service centre and call centre were developed using the concepts of maturity index on reliability. The results showed that the structure of the information handling process resulted in a massive data loss (up to 60% of the data gathered by the service centres) and also in serious data quality degradation. Would this information have not been lost, it could have been used by development teams for preventive and corrective actions. Copyright © 2004 John Wiley & Sons, Ltd.     

Rendering fireworks displays

A particle system technique to model, render, and animate realistic fireworks displays is presented. The attributes of the fireworks display that the particle system models are color, brightness, shape, trial, size, particle dynamics, blinking, mousing, star effect, spinning, and elasticity. A rendering engine that consists of various modules which individually handle a particular property of the particle is described     

Slope stability evaluation using neural network optimized by equilibrium optimization and vortex search algorithm

A dependable evaluation of the stability of slopes is a prerequisite in many construction projects. Although machine learning models have been satisfactorily used for this purpose, combining them with metaheuristic optimizers has resulted in a larger accuracy. This study, therefore, suggests the use of equilibrium optimization (EO) and vortex search algorithm (VSA) for optimizing a multi-layer perceptron neural network (MLPNN) employed to anticipate the factor of safety of a single-layer soil slope. Two hybrid models, as well as the regular MLPNN, are fed by a total of 630 data acquired from finite element simulations. The results, first, showed the applicability of artificial intelligence in this field. Next, reducing the training root mean square error (RMSE) of the MLPNN (from 0.4715 to 0.3891 and 0.4383 by the EO and VSA, respectively) revealed the efficiency of the used algorithms in remedying the computational weaknesses of this model. Moreover, the testing RMSE declined from 0.5397 to 0.4129 and 0.5155, which indicates a higher generalization ability of the hybrid models. Furthermore, due to the larger accuracy of the EO-based ensemble, this algorithm outperformed the VSA in optimizing the MLPNN.